Kenya Disability Dashboard

Statistics from the 2019 Kenya Population and Housing Census

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Key Finding

According to the 2019 census, 2.2% (0.9 million people) of Kenyans live with some form of disability, with mobility difficulties being the most common.

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Summary

National Average (): %

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Distribution Analysis

Regional Patterns

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County Clustering Analysis

Group counties based on similarity across all disability domains using K-means clustering.

Key Insights from 2019 Census Report

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Significant Underreporting

The 2019 census recorded a disability prevalence rate of 2.2%, which is significantly lower than the WHO's global estimate of 15%. This suggests substantial underreporting or methodological issues in data collection.

Potential causes: Stigma, translation issues, inclusion of "Don't know" option, and exclusion of children under 5.

Methodological Changes

The 2019 census introduced the Washington Group Questions, representing a significant improvement in disability measurement methodology. However, this change makes direct comparison with the 2009 census problematic.

2009 vs 2019: The 2009 census reported 3.5% prevalence, but when adjusted for the same age threshold (5+ years), it was actually 3.8%.

Gender and Geographic Disparities

Gender: Women report higher disability rates (2.5%) compared to men (1.9%), reversing the trend from 2009 where rates were more similar (3.7% men vs 3.9% women).

Urban-Rural Divide: Rural areas have nearly double the disability prevalence (2.6%) compared to urban areas (1.4%).

Regional Distribution Patterns

Disability prevalence shows clear geographic patterns:

  • Highest: Central, Eastern, and Western regions (Embu: 4.4%, Homa Bay: 4.3%)
  • Lowest: North Eastern region and Nairobi (Wajir: 0.6%, Nairobi: 1.1%)

This distribution may reflect both actual prevalence differences and varying levels of reporting accuracy.

Methodological Improvements

Washington Group Questions: The 2019 census used internationally comparable questions focusing on functional difficulties across six domains.

Training: Enumerators received sensitivity training and guidance on proper administration of disability questions.

Technology: Kenya's first paperless census improved data collection efficiency.

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Domain-Specific Prevalence

Mobility difficulties are the most common disability type (0.4 million people, 42% of people with disabilities), followed by:

  • Seeing difficulties: 36%
  • Cognition difficulties: ~30%
  • Hearing difficulties: ~25%
  • Self-care difficulties: ~20%
  • Communication difficulties: 12%

Data Quality Concerns

Translation Issues: Questions translated into local languages may have lost nuance, potentially affecting response accuracy.

Stigma: Cultural stigma around disability may have led to underreporting, despite enumerator training.

Albinism Question: Inclusion of albinism in the disability section may have confused respondents, as it's not a functional disability.

"Don't Know" Option: Non-standard inclusion of this response option may have reduced reported prevalence rates.

Policy Implications

Resource Allocation: Underreporting could lead to inadequate funding for disability services and programs.

COVID-19 Response: Inaccurate data hampers effective targeting of vulnerable populations during the pandemic.

Future Planning: The Washington Group framework provides a foundation for improved future data collection and comparability.

DPO Involvement: Organizations of persons with disabilities played a crucial role in advocating for better data collection methods.

Intercensal Comparison

Correlation Matrix

Export Analysis

Data Source: Kenya National Bureau of Statistics - 2019 Kenya Population and Housing Census

Analysis based on "Status of disability in Kenya: Statistics from the 2019 census"